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b68c11e2 · Koen van der Veen · 6a29b1d0 · b68c11e2 · b68c11e2 · b68c11e2
Commit b68c11e2 authored 3 years ago by Koen van der Veen
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+12 -7
--- a/README.md
+++ b/README.md
@@ -54,9 +54,11 @@ client.create(dog)

 After installation, users can use the plugin CLI to manually run a plugin. For more information on how to build a plugin, see `run_plugin`.

+<b>With the pod running, run : </b>
+
 ```bash
-run_plugin --pod_full_address=<pod_address> --plugin_run_id=<plugin_run_id> --owner_key=<owner_key> \
-            --database_key=<dabase_key>
+store_keys
+run_plugin --config_file="example_config.json"
 ```

 ## Docs

--- a/docs/index.html
+++ b/docs/index.html
@@ -107,14 +107,15 @@ client.create(dog)</code></pre>
 <div class="cell border-box-sizing text_cell rendered"><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
 <p>After installation, users can use the plugin CLI to manually run a plugin. For more information on how to build a plugin, see <a href="/pymemri/plugin.pluginbase.html#run_plugin"><code>run_plugin</code></a>.</p>
+<p><b>With the pod running, run : </b></p>

 </div>
 </div>
 </div>
 <div class="cell border-box-sizing text_cell rendered"><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<div class="highlight"><pre><span></span>run_plugin --pod_full_address<span class="o">=</span>&lt;pod_address&gt; --plugin_run_id<span class="o">=</span>&lt;plugin_run_id&gt; --owner_key<span class="o">=</span>&lt;owner_key&gt; <span class="se">\</span>
-            --database_key<span class="o">=</span>&lt;dabase_key&gt;
+<div class="highlight"><pre><span></span>store_keys
+run_plugin --config_file<span class="o">=</span><span class="s2">&quot;example_config.json&quot;</span>
 </pre></div>

 </div>

--- a/nbs/index.ipynb
+++ b/nbs/index.ipynb
@@ -109,7 +109,9 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "After installation, users can use the plugin CLI to manually run a plugin. For more information on how to build a plugin, see `run_plugin`."
+    "After installation, users can use the plugin CLI to manually run a plugin. For more information on how to build a plugin, see `run_plugin`.\n",
+    "\n",
+    "<b>With the pod running, run : </b>"
   ]
  },
  {
@@ -117,8 +119,8 @@
   "metadata": {},
   "source": [
    "```bash\n",
-    "run_plugin --pod_full_address=<pod_address> --plugin_run_id=<plugin_run_id> --owner_key=<owner_key> \\\n",
-    "            --database_key=<dabase_key>\n",
+    "store_keys\n",
+    "run_plugin --config_file=\"example_config.json\"\n",
    "```"
   ]
  },

 %% Cell type:code id: tags:

 ``` python
 # hide
 from pymemri import *
 from pymemri.plugin.pluginbase import run_plugin
 ```

 %% Cell type:markdown id: tags:

 # pymemri

 > Pymemri is a python library for creating <b>Plugins</b> for the Memri Personal online datastore [(pod)](https://gitlab.memri.io/memri/pod). Pymemri has a PodClient to communicate with the pod, and tools to build and test plugins.

 %% Cell type:markdown id: tags:

 [![Gitlab pipeline status (self-hosted)](https://img.shields.io/gitlab/pipeline/memri/pymemri/dev?gitlab_url=https%3A%2F%2Fgitlab.memri.io&label=CI&logo=gitlab&style=plastic)](https://gitlab.memri.io/memri/pymemri/-/pipelines/latest)
 [![Discourse status](https://img.shields.io/discourse/status?color=00A850&label=Discourse&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAhCAYAAAC4JqlRAAAEhUlEQVR42r2XA5RjyxqFM7Y90ymd6uCNbdu2bdu2bdu2bdu27dmvUtfpk9zu5K6utXZU+Pb/l3IsISlCiFiCiBKS0m4GpdMNxpa5JCmbZFDeQTKWR0oZyfJfF8l5IQVdr6DfDcrwL3qnDM3knKf2GyysIoMacKcSfNAvg7AllNIkvrDDCMJ6uQZRgj9S2Xjpmppgk1MlShRNULrcD6iZvhqM1QkOP5xqvMnTQIFKJQlHZ6WhAQJDrALtrFz/JoNjhLHaXumqwRizjjYlF/S4gt5PZuAst+Fk9lS4UDg9LhRJj9O502B3quTowARs3k18Vusqo/lKJ7yiWafsCrwtwMA9BT6eISWe106DtzUF3jV04kP/Avg0tQo+z6iGj0OK4nXzzDhSMRtyO6Q3E3ftdnuMf8CTJ08eUVXccG+ck3KcVPArARL3q2XS4A/dc+DboT7Ah2XA11X/1JeV+HFxFB6Pr4Y6xTJ4McF7/jP1lLZ3b+RQ2quivqrgz2upqOtIfN3YVkPcwKa6cmwASlXO7vGsMAwjoYar/RFe/fDIvVF/K9dpf1g9A97WDcT3k4NNQN7V52B3JM+R0dSEIKz3n6ece2VypYvJBI5nTKXT/m1755DCtZ68W4hMi1pABDqCmiDs2u/p5yPcK+sSHT1e1EmDj4MK+wL/U0V3tQBp1R2mu4sQoQywPe4Vo6wcp6RdR68WlV8Gep/tDT57CLg9RdBpoLS6y8BD94qFAQKncqfF+/aZ/lx0vmrejRGwL2uJBJXbmmSB9nMZ+OxesUoZuFwqo9rjlf2Bay25NQpyTX3E6LbQbB1MsZjNzXSrwNVymfB1XSu/DYy/MhBsdW1EGnfILAPzTA30JBwX1EHydUt7vw00PtYRtlWNEHHSCbMMTDY1kJcwfex+WdnML/ivrythXVcN9sVdEGnM/iAcyVgfbcBMa41AfJhYyS8Da++OhWVpacSbOR8xuswxux2reDRQmnBcq5UT+LzCJ/hX1S/VljoIWF0DlpUvkLB8syAMIQTxaCA/5bhcMSt+vV3ik4FWx7vo6BPMnoqwi+6bnIb0vEUVjwaaE4EXE2v4BO9+uqeG25a1hWXVa8Sr3cvsLujs1cC0XGnw8+bEEIHvv12A4nuaa7h9RUtYVjxB5JG7Ibh0j/65lDKmVwNbmxX/x+A/v6zCroeTsPX+BLz7uPTP31+9X4z1d8eh7pH2iLS8HKIsLw86b7CK/CUiTjwG7kxttvrbargnA4FKN1d21YAjj6ei9f4+SL+0M6yzh4HMHq73dZxVlRB1RXkdbfhlZcFW14FY0BfhF17QaY/RbQG4zWn2L/kyYyyyVwNZUjoxeHpHFOrVGLJuQyQpVA3WTHkhpB0sZQbEbjEG4WddRvhF55QuqVX+REPDLnqA6L2WICBncc8PLYT8T4PdDPgkki4HkuUpg6QFKsGaOR+ECPTW/ofBWBkN9cGAXxKUfZCMldbAUDdA2D1JaVoNC10D+mlo7J/bLfQM0PuSsMH6mA1OUS6n+iNB+UQF7a8+15aEJLeEsPwfm4dbxw/8yD4AAAAASUVORK5CYII=&server=https%3A%2F%2Fdiscourse.memri.io)](https://discourse.memri.io)
 [![Twitter URL](https://img.shields.io/twitter/url?label=%40YourMemri&logo=twitter&style=plastic&url=https%3A%2F%2Ftwitter.com%2FYourMemri)](https://twitter.com/YourMemri)

 %% Cell type:markdown id: tags:

 Plugins connect and add the information to your Pod. Plugins that <b>import your data from external services</b> are called **Importers** (Gmail, WhatsApp, etc.). Plugins that <b>connect new data to the existing data</b> are called  **indexers** (face recognition, spam detection, object detection, etc.). Lastly there are plugins that <b>execute actions</b> (sending messages, uploading files). This repository is built with [nbdev](https://github.com/fastai/nbdev), which means that the repo structure has a few differences compared to a standard python repo.

 %% Cell type:markdown id: tags:

 ## Installing

 %% Cell type:markdown id: tags:

 ### As a package
 ```bash
 pip install pymemri
 ```

 %% Cell type:markdown id: tags:

 ### Development
 To install the Python package, and correctly setup nbdev for development run:
 ```bash
 pip install -e . && nbdev_install_git_hooks
 ```
 The last command configures git to automatically clean metadata from your notebooks before a commit.

 %% Cell type:markdown id: tags:

 ## Quickstart: Pod Client

 To use the pymemri `PodClient`, we first need to have a pod running. The quickest way to do this is to install from the [pod repo](https://gitlab.memri.io/memri/pod), and run `./examples/run_development.sh` from within that repo.

 ```
 from pymemri.data.schema import *
 from pymemri.pod.client import *

 class Dog(Item):
    def __init__(self, name, age, id=None, deleted=None):
        super().__init__(id=id, deleted=deleted)
        self.name = name
        self.age = age

    @classmethod
    def from_json(cls, json):
        id = json.get("id", None)
        name = json.get("name", None)
        age = json.get("age", None)
        return cls(id=id,name=name,age=age)

 client = PodClient()
 example_dog = Dog("max", 2)
 client.add_to_schema(example_dog)
 dog = Dog("bob", 3)
 client.create(dog)
 ```

 %% Cell type:markdown id: tags:

 ## Quickstart: Running a plugin

 %% Cell type:markdown id: tags:

 After installation, users can use the plugin CLI to manually run a plugin. For more information on how to build a plugin, see `run_plugin`.

+<b>With the pod running, run : </b>
+
 %% Cell type:markdown id: tags:

 ```bash
-run_plugin --pod_full_address=<pod_address> --plugin_run_id=<plugin_run_id> --owner_key=<owner_key> \
-            --database_key=<dabase_key>
+store_keys
+run_plugin --config_file="example_config.json"
 ```

 %% Cell type:markdown id: tags:

 ## Docs

 - [pymemri docs](http://memri.docs.memri.io/pymemri/pod.client.html#File-API)
 - [plugin tutorial](https://blog.memri.io/getting-started-building-a-plugin/)

 %% Cell type:markdown id: tags:

 ## Nbdev & Jupyter Notebooks
 The Python integrators are written in [nbdev](https://nbdev.fast.ai/) ([video](https://www.youtube.com/watch?v=9Q6sLbz37gk&t=1301s)). With nbdev, it is encouraged to write code in
 [Jupyter Notebooks](https://jupyter.readthedocs.io/en/latest/install/notebook-classic.html). Nbdev syncs all the notebooks in `/nbs` with the python code in `/pymemri`. Tests are written side by side with the code in the notebooks, and documentation is automatically generated from the code and markdown in the notebooks and exported into the `/docs` folder. Check out the [nbdev quickstart](wiki/nbdev_quickstart.md) for an introduction, **watch the video linked above**, or see the [nbdev documentation](https://nbdev.fast.ai/) for a all functionalities and tutorials.

 %% Cell type:code id: tags:

 ``` python
 ```